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Welcome to Aptude's blogging center! Our blogs are written by experts in each respective field. We hope any information gathered in these articles will be beneficial to you and your company. For more information about how we can assist you with your IT Staffing, IT Consulting, or Software Development needs please give us a call at (630) 692-6700!

It’s that time of year again. The worst of winter is behind us; spring is just around the corner; there’s magic in the air. That’s right, it’s Magic Quadrant season! The Oscars of data analytics just dropped like a new album.
I, for one, was salivating to read Gartner’s latest update to their “Magic Quadrant for Analytics and Business Intelligence Platforms” in it’s entirety, all 30k+ words, at least a few times through. Yes, I’m painfully aware of how pathetic that sounds. <sigh> You probably have better things to do with your time, so I’m going to boil it down to the key points for you so that you don’t have to spend a Saturday night curled up with your tablet. (If you’re a nerd like me and still want to read the full report, and it’s worth the read, you can purchase a copy through Gartner. Or if you just...

We’ve all heard the tired cliché, ‘work smarter, not harder’. It’s oft repeated because it speaks to the value of operational efficiencies to maximize deliverables with minimal effort and/or investment. It doesn’t only apply to our own efforts and the work of our teams; it also applies to how we use resources, including technology. It can be extremely tempting when you first get your hands on a ‘new toy’, or in this case increased analytics capabilities, to go from zero to overkill faster than you can say cloud-based relational database engine. But just like our waistlines and our golf scores, sometimes less is more.
Don’t get me wrong, I’m a data nerd, I wrangle massive data sets for fun, just to see what I’ll find. (Don’t judge. Some people play Sudoku; I analyze data.) I do happen upon little gems of unique insights while aimlessly swimming in oceans of big data,...

We’ve all been there, tasked with transforming an utterly useless file into a data set that can be used and analyzed. My most infuriating example was a data set provided as two 1,500 page pdfs. Yes, you read that correctly, two 1500 page pdfs! What is anyone supposed to do with a pdf?!? It gets worse than that, though. The necessary data was formatted into three columns. Data fields would break randomly across lines. Some, but not all, contained characters like ¨or * between fields. There was no uniformity to the fields present for each entry or the order they were in. That was in my pre Power BI days, PPBI if you will. I had to copy the pdf file and paste is as Unicode text into a Word doc, where I removed the columns and irritating characters, then into Excel where the transformation took place. It took several days,...

I’ll admit it, I’m a diehard Excel user. I get excited by the capabilities of nested functions and I consider a well crafted pivot table a work of art. I’ve learned the data limits of a spreadsheet the hard way (1048576 rows by 16384 columns, in case you were wondering). I take pride in building a workbook that allows me to import data and instantly transform it into useful visualizations. I just might be a little bit stubborn; I didn’t really want to leave the familiarity and comfort of a tool that I’ve used for so long and know so well.
Fortunately, I might also be a little bit lazy, which drives me to employ efficiencies and work smarter wherever possible to minimize the amount of work I have to do. When I realized just how simple Power BI is to use, and how, well, powerful its visualization capabilities are, I...

In July, I had created a post about Power Bi vs Tableau for BI data visualization. The race between Power BI and Tableau is rather close, as is evident from the Gartner’s Magic Quadrant 2017. However, you must have noticed that there’s another player in the Leaders’quadrant – QlikView. While its scores on ‘ability to execute’and ‘completeness of vision’could do better, QlikView is certainly a solution to watch out for. But is it better than Power BI? Not in my opinion. If you are about to choose a BI solution for your organization and are wondering which solution to go ahead with – Power BI or QlikView – let me make the choice easier for you.
QlikView – Offers flexibility and simplicity and yet…
QlikView is one of the most flexible Business Intelligence platforms in the world. Qlikview’s USP ‘The Associative Experience’. They enable users to gain unexpected business insights by...

The confusion and the ensuing debate is understandable. Just as organizations were adjusting to dealing with Big Data concepts and terminologies, there has been a spurt of intermingling of new and not so new concepts, such as the use of Data Lakes for Business Intelligence. I can hear some of you thinking: “Are these two even compatible?”, “Isn’t Business Intelligence meant to use Data Warehouses?”, or, “Is this just another new-fangled experimental setup that is likely to hit my bottom-line?” Hold on. That’s a lot of questions.
Let’s first get down to the basics.
What’s exactly is a Data Lake?
Techopedia explains: The data lake architecture is a store-everything approach to big data. Data are not classified when they are stored in the repository, as the value of the data is not clear at the outset. As a result, data preparation is eliminated. A data lake is thus less structured compared...

Photo by rawpixel.com on Unsplash
DevOps is one of the biggest new trends, while BI continues to be in demand. Can we get them to play well with each other?
It is true that DevOps is more common to the Big Data environment. Both are fairly recent innovations (at least in relevance to the concept of technology). Big Data, by definition, has enormous volume and movement of live data passing through. The DevOps approach attempts to keep production relevant by bridging the gap between development and operations.
Business Intelligence, in contrast, deals with batches of data. The success of a BI implementation can only be measured by the extent of its adoption across the enterprise; the depth to which it is being used by the employees; and the improvement it brings in business decisions.
Both – Big Data Analytics and Business Intelligence – depend on one organizational trait that defines their output quality. It...

A Business Intelligence (BI) tool is a must for any businesses keen on making data driven decisions. If you are struggling to decide on a BI tool, you will not be short on choices. After all, the market is flooded with self-service BI tools such as Cognos, SAS, Oracle, Microstrategy, IBM, ThoughtSpot, and Qlik to name a few. The latest Gartner Magic Quadrant for BI tools simplifies the decision by pruning the list of contenders to just two – Tableau and Microsoft’s Power BI. While Microsoft’s Power BI fares better in completeness of vision, Tableau scores slightly on overall ability to execute. The competition is close. Making a decision can still be tricky!
Let me help you out by advocating Microsoft Power BI over Tableau. While, yes, Tableau is perceived as the ‘the modern BI market leader’ still a bit ahead of Power BI in overall execution, but in my honest...

The demand for Business Intelligence (BI) in the transportation industry is palpable. Tackling volatile costs, tighter regulations, and the pressure to chase sustainability, requires transportation companies to leverage data to identify and snap up opportunities for growth. While increasing liberalization and globalization have opened new avenues for expansion for transportation companies, they also need to understand and tackle evolving geo-political regulations and risk due to heightened exposure to factors not under their control.
Business Intelligence has proven to be exceptionally useful to tackle such challenges. It helps companies gain clarity about their transportation costs, and hence give them the ability to control it more effectively. BI also helps them identify negative trends and pre-empt them before their impact is felt, while also providing them with the opportunity to explore opportunities through the analysis of alternate scenarios. Naturally, BI for transportation is not a new phenomenon. In case you want to know...

In our last blog on BI trends to watch we touched on the exciting prospect of Natural Language Processing (NLP) becoming a tool for building queries in business intelligence. Advances in NLP are giving rise to potentially groundbreaking technology, and the subject deserves more than a cursory glance. In this blog we’ll explore some of the pitfalls, challenges and barriers that have kept NLP out of BI, as well as some of the exciting possibilities of its application as BI developers begin to integrate NLP into BI.
If search engines like Google have been using NLP technology for the past couple of years, why is BI only beginning to make use of this incredible tool? Clearly it’s not for lack of interest, demand, or potential applications. Bridging the chasm between human language and machine language is far more complicated than one might imagine. Computer scientists have been racking their brains over...

Now that we’re solidly in Q2 2017 we’re looking at emerging trends and what to watch for in Business Intelligence for the remainder of the year. This year appears to be focused on expansion, integration and collaboration, as well as some interesting advances in the field. Many of the trends we reported on from 2016 continue to factor heavily in the market, as do new iterations of familiar concepts and ubiquity of BI applications. BI functions that were once only available to large organizations are becoming available to small businesses through cloud-based applications and services like AWS and Microsoft Azure, and BI products are becoming ever more user friendly so that they are available to more individuals.
Self-Service Data Prep
BI continues to move out of the realm of IT and analysts and into the hands of end users. Self-Service Data Procurement has become commonplace and has allowed those in various...

If you’re a left-brained, analytical thinker, like I am, then you love the efficiency and consistency that universal processes can deliver. I’m system-oriented, and will develop procedures, templates, and process flows for almost everything I do. It requires an initial investment of time and effort, but the return is that I deliver better results, more quickly, and I free-up mental space (creative capital) for other uses.
ITIL Process Management has the potential to similarly affect your entire IT infrastructure, and thus your BI. The focus is on a systematic, proactive approach to eliminating root problems, and minimizing reactively (and repeatedly) addressing individual incidents while simultaneously allocating IT resources to those places they are most needed and will yield the greatest returns.
I’m not going to dive into the details of ITIL in this blog, so if you’re not familiar with ITIL there are plenty of short videos available to give you...

2016 was a big year for business intelligence. The field began an evolution into a new iteration of analytics as innovations in hardware and software enabled both greater capacity for data collection and greater ability to interpret that data. We’ve seen BI continue migrating to cloud computing and remote devices. We’ve witnessed a rise in the use of operational intelligence (OI) to gather real-time data on manufacturing machines, vehicles, and warehouses. We’ve watched the Internet of Things (IoT) expand exponentially as OI and connected devices continue to provide an ever expanding field of data. And we’ve watched artificial intelligence (AI) become more integrated into daily life and into the workplace.
As we come to the close of a wild year, in so many ways, let’s take a look back at some of the most influential advances in BI over the last 12 months
Notable Updates and Upgrades
All the biggest players...

Business intelligence (BI) has revolutionized logistics and transportation, and the rate of change is only increasing. Before we look at where the industry is headed, though, let’s take a moment to look at how far it’s come.
The concepts of logistics and transportation are as old as trade itself. The term logistics was first used in the early 1800’s to describe the calculated movement of troops during conflict and from there the idea was transferred to business as the management of the movement of raw materials to production and finished goods from production to market. Logistics and transportation have always been focused on the best means of moving people and goods from origin to destination, but prior to BI the emphasis was on geography and available infrastructure. Clearly things have changed since those humble origins.
Early applications of BI in logistics and transportation relied on descriptive analytics to provide information about...

Business Intelligence (BI) dashboards, or enterprise dashboards, are collections of infographics representing a snapshot of data from various sources about an organization and/or industry in real time. They are intended to provide access to up-to-date, relevant information that allows users to make the most informed decisions within a business. Like anything in life, whether that goal is achieved depends upon the implementation.
A well-designed dashboard gives the right information to the right people within an organization in a format that makes sense the user. It can streamline decision making, allow for more sophisticated analyses of data sets, provide real-time insights into what is and is not working within an organization and inform decisions to maximize gains and limit losses. With poor implementation the end result could be the quite the opposite.
So how do you design a dashboard that meets the needs of your organization?
One way is to carefully define...

Our last blog about implementing microservices for Big Data applications had me thinking about how well two of the biggest names in Business Intelligence – Microsoft and Oracle – compare with their RESTFul API offerings.
Creating your own API services can be quite challenging, even with the large number of software platforms available to choose from to help expedite implementation. Some of the big challenges include coordinating teams to standardize data formats, ensuring scalability, and maintaining data quality.
While both Microsoft and Oracle provide solutions for reporting from databases in their own respective dashboard solutions, and have pre-built connectors for common enterprise solutions (such as Salesforce or Big Data platforms), other services will always require a method to consume your data. This can include a handful of your in-house or 3rd-party applications, or external sources such as a vendor or partner.
Using the Oracle and Microsoft RESTFul API’s are supposed provide...

While implementation of DevOps practices has been on the rise lately, a slightly lesser-known concept has also been gaining popularity – microservices. The idea behind microservice architecture is to build your application as many independent services rather than one large code base (commonly referred to as a monolith). Rather than accessing the majority of your data using large databases, communication is often handled with API calls between the services, with each service having its own lightweight database.
Microservice architecture doesn’t necessarily mandate any more than the core concepts mentioned above, but there are many other best practices that help facilitate better integration across many facets of software development lifecycles. The primary practices associated with microservices include containerization, continuous integration, DevOps, automated integration testing, and – in many cases- the Agile development methodology.
When implemented properly in combination with these best practices, implementation of microservices can deliver many benefits to your project’s...

Microsoft’s initiatives to make Power BI user-friendly and easy to configure have helped propel it to the forefront of BI/Data Analytics solutions, according to an early 2016 release by Gartner. A big proponent of this success can likely be attributed to healthy selection of data connectors which allow accessing data sources from popular services without the need to develop custom web services.
This capability is much more than being able to access all of your data in one dashboard. If your marketing and sales data sources are connected to Power BI, you can correlate metrics across platforms and attribute changes from each-other. By having a more complete view of your data, the likelihood of attributing “false positives” is also reduced.
Connecting these data sources and making informed decisions - whether you’re using Power BI or not – is the true goal of any business intelligence solution. For the Power BI...

As of June of this year, Microsoft SQL Server 2016 – Microsoft’s database management software – has been unleashed for commercial use. There are many new features that enterprises will benefit from that its predecessor didn’t offer or lacked. This beefed up suite of features will have new users grinning from ear to ear. Here is why your organization needs to make the switch to the new and improved SQL Server.
Home is where your data is...
SQL Server 2016 is blowing the roof off of data access and how fast data analysis is performed. Why? Updating machine learning models, deploying new models, and monitoring performance can be done in the database without redeploying applications. R Services (In-database) allows users to to use the R language and packages to create models and generate predictions using your SQL Server data. R Services (In-database) integrates the R language with the SQL Server which...

In July, Microsoft Power BI Desktop made several data-driven updates including a major one - Power BI Embedded. To recap, Power BI is a desktop program you can download and a cloud service that have different and overlapping capabilities for organizations to get the most out of their collected business analytics. Something to be aware of, while Power BI’s desktop software is a powerful tool to have, it’s for Windows-only users - at least for now. The Power BI cloud service on the other hand functions across many platforms. How an organization analyzes their collected data is vital to the success and future of their business. Power BI continues to add features to beef up their tools, especially when it comes to how organizations are monitoring and analyzing their data.
Power BI Embedded
This update will be very useful. What is it? Power BI Embedded is an Azure service that allows...

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